Multimedia data (video, audio, text, and combinations thereof) used by many applications presents a large degree of complexity. In many applications, such complexity is primarily addressed through data compression to achieve efficient processing, delivery, presentation, and other important functions involving the multimedia data.
Data compression algorithms rely upon the redundancy in a data set to obtain coding efficiency. In general, a priori knowledge of the characteristics of data sets are used to select coding algorithms for the data sets to achieve data compression. For example, image compression algorithms rely upon spatial correlation in image data. Specifically, it is known that the level of a respective pixel is closely related to the level of adjacent pixels. Likewise, a level of a pixel in a respective video frame is closely related to the level of the same pixel and/or adjacent pixels in a prior video frame. Accordingly, many image and video compression algorithms generate “residual” or “difference” signals that are encoded using run lengths and other techniques to take advantage of the spatial and/or temporal correlation. For example, the compression algorithms defined by the Motion Picture Expert's Group (MPEG) standards use these techniques.
The performance of a compression algorithm is dependent upon the choice of the reference mechanism or functionality used to generate the residual signal. In video compression algorithms, the selection of the reference frame occurs by assuming that a relatively restrictive temporal relationship exists. Following this assumption, the reference frame is typically selected by examining a limited number of previous frames from a frame being encoded. If the video data exhibits a relatively tight temporal correlation, compression performance is acceptable. However, multimedia data does not necessarily always follow such assumptions. Accordingly, known compression algorithms may not be able to effectively exploit the redundancy that exists in many multimedia data sets.